fix #5 #10 bot not giving expected response or unhashable type dict

AI-engine/data/sitebot-data.json

@@ -173,7 +173,7 @@
                     {
                     "start": 52,
                     "end": 57,
-                    "value": "tomorrow 10 PM",
+                    "value": "10 PM",
                     "entity": "time"
                     },
                     {

bot-application/app.py

@@ -14,7 +14,9 @@ def hello_world():
     return render_template('home.html')
 
 
-get_random_response = lambda intent: random.choice(response[intent])
+def get_random_response(intent):
+    print (response[intent])
+    return random.choice(response[intent])
 
 
 def format_entities(entities):
@@ -52,19 +54,20 @@ def chat():
     chat end point that performs NLU using rasa.ai
     and constructs response from response.py
     """
-    try:
-        response = requests.get("http://localhost:5000/parse", params={"q": request.form["text"]})
-        response = response.json()
-        intent = response["intent"]
-        entities = format_entities(response["entities"])
-        if intent == "event-request":
-            response_text = get_event(entities["day"], entities["time"], entities["place"])
-        else:
-            response_text = get_random_response(intent)
-        return jsonify({"status": "success", "response": response_text})
-    except Exception as e:
-        print(e)
-        return jsonify({"status": "success", "response": "Sorry I am not trained to do that yet..."})
+    # try:
+    response = requests.get("http://localhost:5000/parse", params={"q": request.form["text"]})
+    response = response.json()
+    print (response)
+    intent = response.get("intent", {}).get("name", "default")
+    entities = format_entities(response.get("entities", []))
+    if intent == "event-request":
+        response_text = get_event(entities["day"], entities["time"], entities["place"])
+    else:
+        response_text = get_random_response(intent)
+    return jsonify({"status": "success", "response": response_text})
+    # except Exception as e:
+    #     print(e)
+    #     return jsonify({"status": "success", "response": "Sorry I am not trained to do that yet..."})
 
 
 app.config["DEBUG"] = True

bot-application/models.py

@@ -1,10 +1,11 @@
 from flask import Flask
 from flask_sqlalchemy import SQLAlchemy
-#from urllib import quote_plus as urlquote
+# from urllib import quote_plus as urlquote
 import urllib.parse
 from flask_admin import Admin
 from flask_admin.contrib.sqla import ModelView
 from flask_migrate import Migrate
+
 try:
     from local_settings import *
 except ImportError:
@@ -15,16 +16,17 @@
 app.config["SQLALCHEMY_TRACK_MODIFICATIONS"] = True
 app.config['SQLALCHEMY_DATABASE_URI'] = "sqlite:///app.db"
 db = SQLAlchemy(app)
-#Migrate won't work well on sqlite better to use mysql db
+# Migrate won't work well on sqlite better to use mysql db
 migrate = Migrate(app, db)
 
 
 class Event(db.Model):
-    id = db.Column(db.Integer, primary_key=True,autoincrement=True)
+    id = db.Column(db.Integer, primary_key=True, autoincrement=True)
     event_description = db.Column(db.String(50))
     date_time = db.Column(db.DateTime())
     place = db.Column(db.String(50))
-    def __init__(self, event_description=None,date=None,time=None,place=None):
+
+    def __init__(self, event_description=None, date=None, time=None, place=None):
         self.event_description = event_description
         self.date = date
         self.time = time
@@ -41,4 +43,3 @@ def __init__(self, model, session, name=None, category=None, endpoint=None, url=
 
 admin = Admin(app, name='rasa-site-bot', template_mode='bootstrap3')
 admin.add_view(MyModelView(Event, db.session))
-

bot-application/response.py

@@ -1,48 +1,59 @@
-##dict of response for each type of intent
+# dict of response for each type of intent
+
+import datetime
+
 response = {
-    "greet":["hey","hello","hi"],
-    "goodbye":["bye","It was nice talking to you","see you","ttyl"],
-    "affirm":["cool","I know you would like it"],
-    "day_preference":["which day of conference ?"],
-    "time_preference":["Do you have any time preference"],
-    "events_link":['You can check all the events here <a href="https://conference.pydelhi.org/#schedule_table">PyDelhi events</a>'],
-    "no_events":["No events found"],
-    "intro":["I am event bot for pydelhi, I can find you event details in minutes"]
+    "greet": ["hey", "hello", "hi"],
+    "goodbye": ["bye", "It was nice talking to you", "see you", "ttyl"],
+    "affirm": ["cool", "I know you would like it"],
+    "day_preference": ["which day of conference ?"],
+    "time_preference": ["Do you have any time preference"],
+    "events_link": [
+        'You can check all the events here <a href="https://conference.pydelhi.org/#schedule_table">PyDelhi events</a>'],
+    "no_events": ["No events found"],
+    "intro": ["I am event bot for pydelhi, I can find you event details in minutes"],
+    "default": ["Sorry I am not trained to answer that yet.", "Oops I didn't understand that sorry"]
 }
-import datetime
+
 mapping = {
-    "now":datetime.datetime.now(),
+    "now": datetime.datetime.now(),
     "tomorrow": datetime.date.today() + datetime.timedelta(days=1),
-    "today":datetime.date.today(),
-    "same time":datetime.datetime.now(),
-    "second day":datetime.datetime.now()
+    "today": datetime.date.today(),
+    "same time": datetime.datetime.now(),
+    "second day": datetime.datetime.now()
 }
 
+
 def try_parsing_date(text):
     """
     Parses time of string format to a time object
     """
     for fmt in ('%I %p', '%I %M %p', '%I:%M %p'):
         try:
             return datetime.datetime.strptime(text, fmt)
-        except ValueError:pass
+        except ValueError:
+            pass
     if ":" in text:
-        return datetime.datetime.strptime(text+" "+
-                ("AM" if int(text.split(":")[0])>=8 else "PM"), '%I:%M %p')
-    return datetime.datetime.strptime(text+" "+
-            ("AM" if int(text)>=8 else "PM"), '%I %p')
+        return datetime.datetime.strptime(text + " " +
+                                          ("AM" if int(text.split(":")[0]) >= 8 else "PM"), '%I:%M %p')
+    return datetime.datetime.strptime(text + " " +
+                                      ("AM" if int(text) >= 8 else "PM"), '%I %p')
 
-def get_date_time(day,time):
+
+def get_date_time(day, time):
     """
     Maps words like now today tom etc., to corresponding datetime objects
     """
-    try:time = mapping[time]
+    try:
+        time = mapping[time]
     except KeyError:
         if not time:
             time = datetime.datetime.now()
         else:
             time = try_parsing_date(time)
-    try:date = mapping[day]
-    except KeyError:date = datetime.date.today()
+    try:
+        date = mapping[day]
+    except KeyError:
+        date = datetime.date.today()
 
     return datetime.datetime.combine(date, time.time())

models/nlu/default/model_20181001-224630/entity_synonyms.json

@@ -0,0 +1,9 @@
+{
+  "10 pm": "tomorrow 10 PM",
+  "tommorrow": "tomorrow",
+  "tomorrow": "2",
+  "6:30 pm": "10 AM",
+  "6 am": "10 AM",
+  "6 30 pm": "10 AM",
+  "after": "before"
+}

models/nlu/default/model_20181001-224630/metadata.json

@@ -0,0 +1,84 @@
+{
+    "rasa_nlu_version": "0.13.5",
+    "trained_at": "20181001-224630",
+    "pipeline": [
+        {
+            "case_sensitive": false,
+            "name": "nlp_spacy",
+            "model": "en",
+            "class": "rasa_nlu.utils.spacy_utils.SpacyNLP"
+        },
+        {
+            "name": "tokenizer_spacy",
+            "class": "rasa_nlu.tokenizers.spacy_tokenizer.SpacyTokenizer"
+        },
+        {
+            "name": "intent_featurizer_spacy",
+            "class": "rasa_nlu.featurizers.spacy_featurizer.SpacyFeaturizer"
+        },
+        {
+            "name": "intent_entity_featurizer_regex",
+            "class": "rasa_nlu.featurizers.regex_featurizer.RegexFeaturizer",
+            "regex_file": "regex_featurizer.json"
+        },
+        {
+            "L2_c": 0.1,
+            "max_iterations": 50,
+            "L1_c": 0.1,
+            "class": "rasa_nlu.extractors.crf_entity_extractor.CRFEntityExtractor",
+            "name": "ner_crf",
+            "classifier_file": "crf_model.pkl",
+            "BILOU_flag": true,
+            "features": [
+                [
+                    "low",
+                    "title",
+                    "upper"
+                ],
+                [
+                    "bias",
+                    "low",
+                    "prefix5",
+                    "prefix2",
+                    "suffix5",
+                    "suffix3",
+                    "suffix2",
+                    "upper",
+                    "title",
+                    "digit",
+                    "pattern"
+                ],
+                [
+                    "low",
+                    "title",
+                    "upper"
+                ]
+            ]
+        },
+        {
+            "name": "ner_synonyms",
+            "synonyms_file": "entity_synonyms.json",
+            "class": "rasa_nlu.extractors.entity_synonyms.EntitySynonymMapper"
+        },
+        {
+            "kernels": [
+                "linear"
+            ],
+            "classifier_file": "intent_classifier_sklearn.pkl",
+            "class": "rasa_nlu.classifiers.sklearn_intent_classifier.SklearnIntentClassifier",
+            "C": [
+                1,
+                2,
+                5,
+                10,
+                20,
+                100
+            ],
+            "max_cross_validation_folds": 5,
+            "scoring_function": "f1_weighted",
+            "name": "intent_classifier_sklearn"
+        }
+    ],
+    "language": "en",
+    "training_data": "training_data.json"
+}

models/nlu/default/model_20181001-224630/regex_featurizer.json

@@ -0,0 +1 @@
+[]